About

Hi, I'm Serhii Smetanskyi — a Software Test & Automation Engineer focused on testing AI systems and building AI automation.

This is my Digital Garden — a knowledge base for QA and Test Automation Engineers, built around best practices, practical guides, and real implementation examples.

Architecture & Design

• API Architectures — REST, GraphQL, gRPC, WebSocket, cross-cutting concerns, decision factors
• Client-Server Architecture — core model, edge layer, traffic/service mesh, scalability, reliability
• Software Design Patterns — OOP, SOLID, DRY/KISS, creational/structural/behavioral patterns
• Agentic AI Architecture — agents, multi-agent patterns, memory/RAG, vectorless RAG, tool integration, context engineering
• AI Skills for Coding Agents — SKILL.md standard, cross-agent compatibility, MCP, AGENTS.md, playgrounds, project structure

Security

• Code Security — secrets, dependency security, SAST, auth/headers, CI/CD monitoring, audit checklist
• OWASP API Security — API Top 10, per-risk controls, OAuth2/webhooks, testing checklists
• OWASP LLM Security — LLM Top 10, prompt injection, agent security, RAG hardening

QA & Testing

• QA Methodology — fundamentals, test design, defects, metrics, TDD/BDD, quality gates, shift-left, shift-right
• Test Design Techniques — EP, BVA, Decision Table, State Transition, Pairwise, Fuzz
• Test Design Patterns — POM, Screenplay, Data Builder, API patterns, mocking, CI/CD
• Testing Pyramid — unit, integration, E2E strategy and anti-patterns
• Test Automation Framework — architecture, patterns, parallel execution, CI/CD
• Robot Framework — syntax, keywords, API/UI testing, parallel execution
• LLM Evaluation — DeepEval: RAG, chatbot, agent, MCP metrics, conversational RAG, red teaming, benchmarks
• Performance Testing — Locust, load/stress/spike testing, SLA/SLO
• Python Guide — complete Python path for Automation QA
• Jenkins Pipeline Guide — Jenkinsfiles, declarative syntax, shared libraries

Infrastructure & Tools

• CI/CD Approaches — pipeline architecture, deployment, security, GitOps
• Databases — PostgreSQL commands, schema, queries, performance
• Tools — Docker, Git, Linux Terminal, Kubernetes
• Python Libraries — Requests, HTTPX, Pytest, Playwright, Pydantic, SQLAlchemy, FastAPI, uv, LangChain